Context Engineering
Context engineering is the practice of selecting, organizing, and maintaining the information a model receives while it works. It includes instructions, tool descriptions, retrieved material, and conversation state.
[Anthropic]In practice · hypothetical example
A travel assistant keeps the current itinerary and budget in view while removing obsolete search results from its next request.
[Anthropic]A little deeper
The task repeats as an agent runs: useful evidence arrives while older material can become irrelevant. The aim is useful context within a finite capacity, rather than simply adding more text. [Anthropic]
A common mix-up
Context engineering means making one prompt longer.
It includes managing changing information across multiple model calls. [Anthropic]
Which change best illustrates context engineering?
Sources & editorial notes
Evidence: supported. Primary-source support for this scoped entry; publication approved by the project owner.
- Effective context engineering for AI agents ↗ (opens in new tab)Anthropic · Publication date unknown
Relevant section: Context engineering vs. prompt engineering; The anatomy of effective context
Last editorial review: 2026-09-13 by project-owner.
First observed in this corpus: Unknown.
Revision history
Revision 2 · Created 2026-09-13 · Updated 2026-09-13
Project owner approved the current content for publication. Existing evidence scope and limitations remain applicable.